Task Scheduling Algorithm Improvement in Cloud Computing

Abstract

Over the past few decades, academics have focused on task scheduling as one of the major issues in the cloud computing environment to enhance resource utilization and achieve cost-effective execution. In cloud computing, task scheduling is the process of allocating the most effective resources to do tasks while accounting for many factors, such as the task's execution time, user priority, cost, scalability, throughput, make-span, resource consumption, and so on. The primary objective of this paper is to give a comparative analysis of multiple Multiple-Criteria-decision-making (MCDM) algorithms in different cloud computing environments. This paper provides an analysis of algorithms like FCFS, AHP, & BWM to provide performance evaluation on various data sets. The results of the experiment demonstrate the advantages of the AHP algorithm, which outperforms other algorithms by getting the least waiting time.